Sterility Examination and Comparative Analyses of Inhibitory Effect of Honey on Some Gram Negative and Gram Positive Food Borne Pathogens in South West Nigeria

Food borne illnesses have been reported to be a global health challenge. Annual incidences of food–related diseases involve 76 million cases, of which only 14 million can be traced to known pathogens. Poor hygienic practices have contributed greatly to this. It has been reported that in the year 2000 about 2.1 million people died from diarrheal diseases, hence, there is a need to ensure food safety at all level. This study focused on the sterility examination and inhibitory effect of honey samples on selected gram negative and gram positive food borne pathogen from South West Nigeria. The laboratory examinations revealed the presence of some bacterial and fungal contaminations of honey samples and that inhibitory activity of the honey sample was more pronounced on the gram negative bacteria than the gram positive bacterial isolates. Antibiotic sensitivity test conducted on the different bacterial isolates also showed that honey was able to inhibit the proliferation of the tested bacteria than the employed antibiotics.

The Optimization of an Intelligent Traffic Congestion Level Classification from Motorists- Judgments on Vehicle's Moving Patterns

We proposed a technique to identify road traffic congestion levels from velocity of mobile sensors with high accuracy and consistent with motorists- judgments. The data collection utilized a GPS device, a webcam, and an opinion survey. Human perceptions were used to rate the traffic congestion levels into three levels: light, heavy, and jam. Then the ratings and velocity were fed into a decision tree learning model (J48). We successfully extracted vehicle movement patterns to feed into the learning model using a sliding windows technique. The parameters capturing the vehicle moving patterns and the windows size were heuristically optimized. The model achieved accuracy as high as 99.68%. By implementing the model on the existing traffic report systems, the reports will cover comprehensive areas. The proposed method can be applied to any parts of the world.

Automated Thickness Measurement of Retinal Blood Vessels for Implementation of Clinical Decision Support Systems in Diagnostic Diabetic Retinopathy

The structure of retinal vessels is a prominent feature, that reveals information on the state of disease that are reflected in the form of measurable abnormalities in thickness and colour. Vascular structures of retina, for implementation of clinical diabetic retinopathy decision making system is presented in this paper. Retinal Vascular structure is with thin blood vessel, whose accuracy is highly dependent upon the vessel segmentation. In this paper the blood vessel thickness is automatically detected using preprocessing techniques and vessel segmentation algorithm. First the capture image is binarized to get the blood vessel structure clearly, then it is skeletonised to get the overall structure of all the terminal and branching nodes of the blood vessels. By identifying the terminal node and the branching points automatically, the main and branching blood vessel thickness is estimated. Results are presented and compared with those provided by clinical classification on 50 vessels collected from Bejan Singh Eye hospital..

A DEA Model for Performance Evaluation in The Presence of Time Lag Effect

Data Envelopment Analysis (DEA) is a methodology that computes efficiency values for decision making units (DMU) in a given period by comparing the outputs with the inputs. In many cases, there are some time lag between the consumption of inputs and the production of outputs. For a long-term research project, it is hard to avoid the production lead time phenomenon. This time lag effect should be considered in evaluating the performance of organizations. This paper suggests a model to calculate efficiency values for the performance evaluation problem with time lag. In the experimental part, the proposed methods are compared with the CCR and an existing time lag model using the data set of the 21st century frontier R&D program which is a long-term national R&D program of Korea.

Causes of Rotor Distortions and Applicable Common Straightening Methods for Turbine Rotors and Shafts

Different problems may causes distortion of the rotor, and hence vibration, which is the most severe damage of the turbine rotors. In many years different techniques have been developed for the straightening of bent rotors. The method for straightening can be selected according to initial information from preliminary inspections and tests such as nondestructive tests, chemical analysis, run out tests and also a knowledge of the shaft material. This article covers the various causes of excessive bends and then some applicable common straightening methods are reviewed. Finally, hot spotting is opted for a particular bent rotor. A 325 MW steam turbine rotor is modeled and finite element analyses are arranged to investigate this straightening process. Results of experimental data show that performing the exact hot spot straightening process reduced the bending of the rotor significantly.

A New Method in Detection of Ceramic Tiles Color Defects Using Genetic C-Means Algorithm

In this paper an algorithm is used to detect the color defects of ceramic tiles. First the image of a normal tile is clustered using GCMA; Genetic C-means Clustering Algorithm; those results in best cluster centers. C-means is a common clustering algorithm which optimizes an objective function, based on a measure between data points and the cluster centers in the data space. Here the objective function describes the mean square error. After finding the best centers, each pixel of the image is assigned to the cluster with closest cluster center. Then, the maximum errors of clusters are computed. For each cluster, max error is the maximum distance between its center and all the pixels which belong to it. After computing errors all the pixels of defected tile image are clustered based on the centers obtained from normal tile image in previous stage. Pixels which their distance from their cluster center is more than the maximum error of that cluster are considered as defected pixels.

A New Ridge Orientation based Method of Computation for Feature Extraction from Fingerprint Images

An important step in studying the statistics of fingerprint minutia features is to reliably extract minutia features from the fingerprint images. A new reliable method of computation for minutiae feature extraction from fingerprint images is presented. A fingerprint image is treated as a textured image. An orientation flow field of the ridges is computed for the fingerprint image. To accurately locate ridges, a new ridge orientation based computation method is proposed. After ridge segmentation a new method of computation is proposed for smoothing the ridges. The ridge skeleton image is obtained and then smoothed using morphological operators to detect the features. A post processing stage eliminates a large number of false features from the detected set of minutiae features. The detected features are observed to be reliable and accurate.

Chemotherapy Safety Protocol for Oncology Nurses: It's Effect on Their Protective Measures Practices

Background: Widespread use of chemotherapeutic drugs in the treatment of cancer has lead to higher health hazards among employee who handle and administer such drugs, so nurses should know how to protect themselves, their patients and their work environment against toxic effects of chemotherapy. Aim of this study was carried out to examine the effect of chemotherapy safety protocol for oncology nurses on their protective measure practices. Design: A quasi experimental research design was utilized. Setting: The study was carried out in oncology department of Menoufia university hospital and Tanta oncology treatment center. Sample: A convenience sample of forty five nurses in Tanta oncology treatment center and eighteen nurses in Menoufiya oncology department. Tools: 1. an interviewing questionnaire that covering sociodemographic data, assessment of unit and nurses' knowledge about chemotherapy. II: Obeservational check list to assess nurses' actual practices of handling and adminestration of chemotherapy. A base line data were assessed before implementing Chemotherapy Safety protocol, then Chemotherapy Safety protocol was implemented, and after 2 monthes they were assessed again. Results: reveled that 88.9% of study group I and 55.6% of study group II improved to good total knowledge scores after educating on the safety protocol, also 95.6% of study group I and 88.9% of study group II had good total practice score after educating on the safety protocol. Moreover less than half of group I (44.4%) reported that heavy workload is the most barriers for them, while the majority of group II (94.4%) had many barriers for adhering to the safety protocol such as they didn’t know the protocol, the heavy work load and inadequate equipment. Conclusions: Safety protocol for Oncology Nurses seemed to have positive effect on improving nurses' knowledge and practice. Recommendation: chemotherapy safety protocol should be instituted for all oncology nurses who are working in any oncology unit and/ or center to enhance compliance, and this protocol should be done at frequent intervals.

Diagnosing the Cause and its Timing of Changes in Multivariate Process Mean Vector from Quality Control Charts using Artificial Neural Network

Quality control charts are very effective in detecting out of control signals but when a control chart signals an out of control condition of the process mean, searching for a special cause in the vicinity of the signal time would not always lead to prompt identification of the source(s) of the out of control condition as the change point in the process parameter(s) is usually different from the signal time. It is very important to manufacturer to determine at what point and which parameters in the past caused the signal. Early warning of process change would expedite the search for the special causes and enhance quality at lower cost. In this paper the quality variables under investigation are assumed to follow a multivariate normal distribution with known means and variance-covariance matrix and the process means after one step change remain at the new level until the special cause is being identified and removed, also it is supposed that only one variable could be changed at the same time. This research applies artificial neural network (ANN) to identify the time the change occurred and the parameter which caused the change or shift. The performance of the approach was assessed through a computer simulation experiment. The results show that neural network performs effectively and equally well for the whole shift magnitude which has been considered.

Ventilation Efficiency in the Subway Environment for the Indoor Air Quality

Clean air in subway station is important to passengers. The Platform Screen Doors (PSDs) can improve indoor air quality in the subway station; however the air quality in the subway tunnel is degraded. The subway tunnel has high CO2 concentration and indoor particulate matter (PM) value. The Indoor Air Quality (IAQ) level in subway environment degrades by increasing the frequency of the train operation and the number of the train. The ventilation systems of the subway tunnel need improvements to have better air-quality. Numerical analyses might be effective tools to analyze the performance of subway twin-track tunnel ventilation systems. An existing subway twin-track tunnel in the metropolitan Seoul subway system is chosen for the numerical simulations. The ANSYS CFX software is used for unsteady computations of the airflow inside the twin-track tunnel when the train moves. The airflow inside the tunnel is simulated when one train runs and two trains run at the same time in the tunnel. The piston-effect inside the tunnel is analyzed when all shafts function as the natural ventilation shaft. The supplied air through the shafts is mixed with the pollutant air in the tunnel. The pollutant air is exhausted by the mechanical ventilation shafts. The supplied and discharged airs are balanced when only one train runs in the twin-track tunnel. The pollutant air in the tunnel is high when two trains run simultaneously in opposite direction and all shafts functioned as the natural shaft cases when there are no electrical power supplies in the shafts. The remained pollutant air inside the tunnel enters into the station platform when the doors are opened.

Existence and Exponential Stability of Almost Periodic Solution for Cohen-Grossberg SICNNs with Impulses

In this paper, based on the estimation of the Cauchy matrix of linear impulsive differential equations, by using Banach fixed point theorem and Gronwall-Bellman-s inequality, some sufficient conditions are obtained for the existence and exponential stability of almost periodic solution for Cohen-Grossberg shunting inhibitory cellular neural networks (SICNNs) with continuously distributed delays and impulses. An example is given to illustrate the main results.

Pulsed Multi-Layered Image Filtering: A VLSI Implementation

Image convolution similar to the receptive fields found in mammalian visual pathways has long been used in conventional image processing in the form of Gabor masks. However, no VLSI implementation of parallel, multi-layered pulsed processing has been brought forward which would emulate this property. We present a technical realization of such a pulsed image processing scheme. The discussed IC also serves as a general testbed for VLSI-based pulsed information processing, which is of interest especially with regard to the robustness of representing an analog signal in the phase or duration of a pulsed, quasi-digital signal, as well as the possibility of direct digital manipulation of such an analog signal. The network connectivity and processing properties are reconfigurable so as to allow adaptation to various processing tasks.

Automatic 3D Reconstruction of Coronary Artery Centerlines from Monoplane X-ray Angiogram Images

We present a new method for the fully automatic 3D reconstruction of the coronary artery centerlines, using two X-ray angiogram projection images from a single rotating monoplane acquisition system. During the first stage, the input images are smoothed using curve evolution techniques. Next, a simple yet efficient multiscale method, based on the information of the Hessian matrix, for the enhancement of the vascular structure is introduced. Hysteresis thresholding using different image quantiles, is used to threshold the arteries. This stage is followed by a thinning procedure to extract the centerlines. The resulting skeleton image is then pruned using morphological and pattern recognition techniques to remove non-vessel like structures. Finally, edge-based stereo correspondence is solved using a parallel evolutionary optimization method based on f symbiosis. The detected 2D centerlines combined with disparity map information allow the reconstruction of the 3D vessel centerlines. The proposed method has been evaluated on patient data sets for evaluation purposes.

Approximate Solution of Nonlinear Fredholm Integral Equations of the First Kind via Converting to Optimization Problems

In this paper we introduce an approach via optimization methods to find approximate solutions for nonlinear Fredholm integral equations of the first kind. To this purpose, we consider two stages of approximation. First we convert the integral equation to a moment problem and then we modify the new problem to two classes of optimization problems, non-constraint optimization problems and optimal control problems. Finally numerical examples is proposed.

Ablation, Mechanical and Thermal Properties of Fiber/Phenolic Matrix Composites

In this study, an ablation, mechanical and thermal properties of a rocket motor insulation from phenolic/ fiber matrix composites forming a laminate with different fiber between fiberglass and locally available synthetic fibers. The phenolic/ fiber matrix composites was mechanics and thermal properties by means of tensile strength, ablation, TGA and DSC. The design of thermal insulation involves several factors.Determined the mechanical properties according to MIL-I-24768: Density >1.3 g/cm3, Tensile strength >103 MPa and Ablation

Site Inspection and Evaluation Behavior of Qing Shang Concrete Bridge

It is necessary to evaluate the bridges conditions and strengthen bridges or parts of them. The reinforcement necessary due to some reasons can be summarized as: First, a changing in use of bridge could produce internal forces in a part of structural which exceed the existing cross-sectional capacity. Second, bridges may also need reinforcement because damage due to external factors which reduced the cross-sectional resistance to external loads. One of other factors could listed here its misdesign in some details, like safety of bridge or part of its.This article identify the design demands of Qing Shan bridge located in is in Heilongjiang Province He gang - Nen Jiang Road 303 provincial highway, Wudalianchi area, China, is an important bridge in the urban areas. The investigation program was include the observation and evaluate the damage in T- section concrete beams , prestressed concrete box girder bridges section in additional evaluate the whole state of bridge includes the pier , abutments , bridge decks, wings , bearing and capping beam, joints, ........etc. The test results show that the bridges in general structural condition are good. T beam span No 10 were observed, crack extended upward along the ribbed T beam, and continue to the T beam flange. Crack width varying between 0.1mm to 0.4mm, the maximum about 0.4mm. The bridge needs to be improved flexural bending strength especially at for T beam section.

Frequency and Amplitude Measurement of a Vibrating Object in Water Using Ultrasonic Speckle Technique

The principle of frequency and amplitude measurement of a vibrating object in water using ultrasonic speckle technique is presented in this paper. Compared with other traditional techniques, the ultrasonic speckle technique can be applied to vibration measurement of a nonmetal object with rough surface in water in a noncontact way. The relationship between speckle movement and object movement was analyzed. Based on this study, an ultrasonic speckle measurement system was set up. With this system the frequency and amplitude of an underwater vibrating cantilever beam was detected. The result shows that the experimental data is in good agreement with the calibrating data.

Optimization of the Characteristic Straight Line Method by a “Best Estimate“ of Observed, Normal Orthometric Elevation Differences

In this paper, to optimize the “Characteristic Straight Line Method" which is used in the soil displacement analysis, a “best estimate" of the geodetic leveling observations has been achieved by taking in account the concept of 'Height systems'. This concept has been discussed in detail and consequently the concept of “height". In landslides dynamic analysis, the soil is considered as a mosaic of rigid blocks. The soil displacement has been monitored and analyzed by using the “Characteristic Straight Line Method". Its characteristic components have been defined constructed from a “best estimate" of the topometric observations. In the measurement of elevation differences, we have used the most modern leveling equipment available. Observational procedures have also been designed to provide the most effective method to acquire data. In addition systematic errors which cannot be sufficiently controlled by instrumentation or observational techniques are minimized by applying appropriate corrections to the observed data: the level collimation correction minimizes the error caused by nonhorizontality of the leveling instrument's line of sight for unequal sight lengths, the refraction correction is modeled to minimize the refraction error caused by temperature (density) variation of air strata, the rod temperature correction accounts for variation in the length of the leveling rod' s Invar/LO-VAR® strip which results from temperature changes, the rod scale correction ensures a uniform scale which conforms to the international length standard and the introduction of the concept of the 'Height systems' where all types of height (orthometric, dynamic, normal, gravity correction, and equipotential surface) have been investigated. The “Characteristic Straight Line Method" is slightly more convenient than the “Characteristic Circle Method". It permits to evaluate a displacement of very small magnitude even when the displacement is of an infinitesimal quantity. The inclination of the landslide is given by the inverse of the distance reference point O to the “Characteristic Straight Line". Its direction is given by the bearing of the normal directed from point O to the Characteristic Straight Line (Fig..6). A “best estimate" of the topometric observations was used to measure the elevation of points carefully selected, before and after the deformation. Gross errors have been eliminated by statistical analyses and by comparing the heights within local neighborhoods. The results of a test using an area where very interesting land surface deformation occurs are reported. Monitoring with different options and qualitative comparison of results based on a sufficient number of check points are presented.

Screening Wheat Parents of Mapping Population for Heat and Drought Tolerance, Detection of Wheat Genetic Variation

To evaluate genetic variation of wheat (Triticum aestivum) affected by heat and drought stress on eight Australian wheat genotypes that are parents of Doubled Haploid (HD) mapping populations at the vegetative stage, the water stress experiment was conducted at 65% field capacity in growth room. Heat stress experiment was conducted in the research field under irrigation over summer. Result show that water stress decreased dry shoot weight and RWC but increased osmolarity and means of Fv/Fm values in all varieties except for Krichauff. Krichauff and Kukri had the maximum RWC under drought stress. Trident variety was shown maximum WUE, osmolarity (610 mM/Kg), dry mater, quantum yield and Fv/Fm 0.815 under water stress condition. However, the recovery of quantum yield was apparent between 4 to 7 days after stress in all varieties. Nevertheless, increase in water stress after that lead to strong decrease in quantum yield. There was a genetic variation for leaf pigments content among varieties under heat stress. Heat stress decreased significantly the total chlorophyll content that measured by SPAD. Krichauff had maximum value of Anthocyanin content (2.978 A/g FW), chlorophyll a+b (2.001 mg/g FW) and chlorophyll a (1.502 mg/g FW). Maximum value of chlorophyll b (0.515 mg/g FW) and Carotenoids (0.234 mg/g FW) content belonged to Kukri. The quantum yield of all varieties decreased significantly, when the weather temperature increased from 28 ÔùªC to 36 ÔùªC during the 6 days. However, the recovery of quantum yield was apparent after 8th day in all varieties. The maximum decrease and recovery in quantum yield was observed in Krichauff. Drought and heat tolerant and moderately tolerant wheat genotypes were included Trident, Krichauff, Kukri and RAC875. Molineux, Berkut and Excalibur were clustered into most sensitive and moderately sensitive genotypes. Finally, the results show that there was a significantly genetic variation among the eight varieties that were studied under heat and water stress.

The Relationship between Burnout, Negative Affectivity and Organizational Citizenship Behavior for Human Services Employees

The purpose of this study was to explore the relationship between Burnout, Negative Affectivity, and Organizational Citizenship Behavior (OCB) for social service workers at two agencies serving homeless populations. Thirty two subjects completed surveys. Significant correlations between major variables and subscales were found.